Evidence map›Paper›PMID 37099200›Full record

ArticleAttention, perception & psychophysics2024

A novel end-to-end dual-camera system for eye gaze synchrony assessment in face-to-face interaction.

Max Thorsson, Martyna A Galazka, Jakob Åsberg Johnels, Nouchine Hadjikhani

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Attention, perception & psychophysics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Max ThorssonGillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. max.thorsson@gu.se.ORCID http://orcid.org/0000-0001-5030-7949
Martyna A GalazkaGillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.ORCID https://orcid.org/0000-0001-6361-370X
Jakob Åsberg JohnelsGillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.ORCID https://orcid.org/0000-0002-3491-5925
Nouchine HadjikhaniGillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.ORCID https://orcid.org/0000-0003-4075-3106

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantification of face-to-face interaction can provide highly relevant information in cognitive and psychological science research. Current commercial glint-dependent solutions suffer from several disadvantages and limitations when applied in face-to-face interaction, including data loss, parallax errors, the inconvenience and distracting effect of wearables, and/or the need for several cameras to capture each person. Here we present a novel eye-tracking solution, consisting of a dual-camera system used in conjunction with an individually optimized deep learning approach that aims to overcome some of these limitations. Our data show that this system can accurately classify gaze location within different areas of the face of two interlocutors, and capture subtle differences in interpersonal gaze synchrony between two individuals during a (semi-)naturalistic face-to-face interaction.

Indexed as

Eye-Tracking TechnologyFixation, OcularAdultDeep LearningFacial RecognitionFemaleHumansInterpersonal RelationsMaleSocial InteractionYoung AdultDeep learningDyadic interactionEye trackingFace-to-face contactInterpersonal synchronization

Identifiers

PMID37099200
PMCPMC11480169

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.